The Database Management and Statistics Core (DMS) formalizes central data management and biostatistical resources and functions that have existed within the Clinical Core since the inception of the Columbia ADRC in 1989. The DMS Core, which was formally established five years ago, is composed of two component and well-coordinated arms, one for biostatistical/epidemiological and the other for data management functions. The Data Management Component will continue to manage a large, highly structured relational database currently containing all clinical evaluation and neuropathological examination data on a large cohort of over 3,800 subjects, including all NACC UDS data collected since the inception of the current UDS . In the proposed funding period the Database Management Component will continue to electronically submit initial and followup UDS packets in the format required by the National Alzheimer's Coordinafing Center (NACC) in a fimely manner, and will serve as a central resource for data, epidemiological and statistical resources to the projects described in this application, as well as to approved collaborations with external investigators and NACC-initiated research projects. The Statistics and Epidemiology Component will work closely with the investigators of each project to design and implement statistical analyses, and to assist in the preparation and review of manuscripts for publication. The Statistics and Epidemiology Component will also confinue to be a resource for collaborative NACC projects and will participate in the design and analysis of collaborative ad hoc research efforts with external and internal investigators. Staff of both components ofthe DMS Core will confinue to participate in weekly, scheduled meetings with leaders of the other cores and projects to review and discuss all data-related issues, including: 1) recruitment and followup ; 2) coordination of data fiow between the clinical and neuropathological cores, and 4) the needs ofthe projects and collaborators for data, stafisfical planning and data analysis.